In this work we propose a behaviour-based architecture, which can also be seen as a multi-agent architecture, to control a situated embodied autonomous mobile robot, under a close sensing action relationship. Pre-existing knowledge can play a meta-level role, being used in order to provide an adviser capability which is combined with the basic reactive feature of the robot. One of the challenges of the behaviour-based approach is the integration and coordination of multiple different behaviours. This problem was faced using combination operators applied to lower level behaviours and producing useful and coherent higher level behaviours. Our autonomous mobile robot also exhibits learning capabilities, namely the ability to learn new behaviours in an autonomous way. In this context it was designed to the elementary behaviours a connectionist architecture that encompasses the capabilities of building specific basic competences. Through the exploration of the proposed control architecture a mobile platform has become an useful autonomous mobile robot. It is able to deal with dynamic environments, evolving in a coherent, relevant and adequate way according to both the current situation as well as with its assigned missions.